Method for interference source identification

ABSTRACT

The present invention relates to a method to identify one or more interference sources in a mobile radio system, preferably in a GSM radio network for mobile telephones. A received signal (r) consists of a wanted signal and a number of interference signals of which one is a dominating interference signal and where all signals includes a known training sequence (TK1,TK2, . . . ). The carrier is estimated and subtracted from the received signal (r) giving a remaining interference signal (s).This signal is correlated against known training sequences (TKj, j=0,1,2, . . . ,7) resulting in a training sequence associated with the interfering signal. According to the invention, the identification code (BCC) of a possible interference source (BS1) from said training sequence is determined. After that, a number of candidates (CA1,CA2, ), each corresponding with a certain cell from the identification code (BCC) are determined and also the frequency which is disturbed and the timing offset (t1,t2, . . .  FIG. 7 ) for the frequencies used by said candidates. Finally it is investigated if one or more (fa,fb) of these have the same time offset as the interference signal (t0) resulting in that at least one candidate (CA3) with the best matching offsets on its frequencies is identified as the interference source.

BACKGROUND OF THE INVENTION

The present invention relates to a method to identify one or moreinterference sources in a mobile radio system, preferably in a GSM radionetwork for mobile telephones.

DESCRIPTION OF PRIOR ART

In a GSM radio network, frequencies must be reused since there is alimited number of frequencies available for a GSM radio networkoperator. The reuse of frequencies causes interference; i.e. the radiosignal received at a certain point is a mixture of the carrier signaland signals from other sources. The carrier signal originates from theserving cell (the cell the mobile has a radio link to) and theinterfering signal often from other GSM cells.

An important task for a GSM radio network operator is to reduce theamount of interference in the network. Clever frequency planning wherefrequencies are reused as sparsely as possible does this. However, sincethe traffic in GSM network increases, the frequencies must be reusedtighter and tighter (with less distance between reuse of a frequency).This cause interference despite clever frequency planning.

When the interference gets too high, there will be problems like droppedcalls, blocking and bad speech quality. In such areas a radio networkoperator wants to find the source of interference and rectify theproblem to improve speech quality and reduce dropped calls. A commontype of interference problem is co-channel interference. The interferingsignal originates from another base station, which belongs to the sameoperator. The interfering base station is using the same frequency asused in the serving cell and causes interference.

The problem solving task, when having problems with co-channelinterference, is normally done like this:

-   -   1. Identify a problem area.    -   2. Go out to the problem area and classify the problem        (interference problem and kind of interference problem, for        example co-channel interference)    -   3. If the problem is a co-channel interference problem the        source of the interference needs to be found.

Step 1 and 2 above are quite straightforward. However, step 3 is not assimple. There can be quite a number of possible base stations from thesame mobile operator that can be the source of the interference. Toidentify the base station or base stations that are the source is acomplicated task.

There are a couple of known methods in this area:

-   -   Measuring of a test signal    -   Correlation against training sequences    -   Carrier estimation (without channel estimation)    -   Using training sequence correlation to find a number of possible        interference sources (base stations)    -   Using a database with time information of received signals. The        information is useful due to the fact that the base station        system is not synchronised in time.

It is previously known see e.g. EP 1 001 565 A2 to identify interferencesignals of a base station in the system of the above mentioned kind bymeasuring the interference signals to the base station and thereafteridentify these by filtering out the pattern sequence components of thereceived signals transmitted by the various base stations in the system.The pattern identifiers are derived from the pattern sequence componentsand a subset of these is matched with the base station's own patternsequence. This known method uses in combination correlation and theregular time slot pattern of a control channel or a regular channel.

SUMMARY OF THE INVENTION

The previous mentioned known solution to correlate against trainingsequences gives false correlation; i.e. noise like correlation peaks.The peaks make the identification of an interference source difficult.

Another known solution uses a database with timing information that mustbe filled with data before the interference source can be found. Work isneeded to keep database up to date. If the database is not kept up todate the information is useless.

Some solutions need continuous sampling of the received signal, whichrequires expensive hardware.

The invention provides a method to identify the source of interferencesignals in a mobile radio network. In the received signal the carriersignal is eliminated, leaving a remaining signal consisting of theinterference signals and noise. The remaining signal is correlated withknown training sequences and the training sequence with the strongestcorrelation is detected. When the training sequence used by each of theinterference sources is identified, it is possible to identify a numberof interference source candidates.

After having identified the above mentioned training sequences and ifthere is more than one candidate, the time offset of the signals on theinterfered frequency and on the frequencies used by the candidates aremeasured and compared. The signal or signals with the same time offsetas the interference signal are identified as originating from theinterference source which results in a set of frequencies. Thecandidates whose frequencies are the same as or best matches thefrequency set are identified as the interference sources.

The method according to the invention is characterized as it appearsfrom the appended claim 1.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will now be described with reference to the encloseddrawings where

FIG. 1 illustrates generally two base stations sending a carrier signaland an interference signal, respectively to a mobile station in a mobileradio system;

FIG. 2 illustrates more in detail cells in a GSM-system where there isinterference problem;

FIG. 3 shows a block diagram of an algorithm according to one feature ofthe present invention;

FIG. 4 shows a diagram of an exemplary correlation to trainingsequences;

FIG. 5 shows a diagram of a the training sequence with the highestcorrelation value plotted over time.

FIG. 6 shows the percentage for a specified time window that a certaintraining sequence has had the strongest correlation; and

FIG. 7 shows a time diagram with interference source candidatesillustrating the candidate elimination.

DESCRIPTION OF PREFERRED EMBODIMENTS

FIG. 1 shows a simplified diagram of a part of a mobile radio system,for instance a GSM system with a sending base station BS0 and aninterfering base station BS1 on near distance from BS0. Only two basestations are shown for the sake of simplicity, however it is understoodthat the system includes several more interfering base stations BS2,BS3,. . . as indicated. Base stations BS0,BS1, . . . are transmitting radiosignals to a mobile station MS which is using the method according tothe present invention. The mobile station MS can be in an operator'svehicle in which equipment using the method of the present invention isinstalled and is managed by educated personnel.

The signals transmitted between the base station BS0 and the mobilestation MS are TDMA-signals transmitted by a carrier, i.e. a determinedfrequency which is one of a number of frequencies characteristic forthat area (cell) which the base station BS0 is serving. The radio signalfrom BS0 is considered to be the wanted signal, while all other signalsare the interfering signals.

As mentioned above, in a GSM radio network, frequencies must be reusedsince there is a limited number of frequencies available for a GSM radionetwork operator. The reuse of frequencies causes interference; i.e. theradio signal received by mobile station MS at a certain point is amixture of the carrier signal from BS0 and signals from another basestation BS1 sending with the same frequency as does BS0. Other basestations can also contribute to interference (not shown here). Thecarrier signal originates from base station BS0, the serving cell (thecell the mobile has a radio link to), and the interfering signal oftenfrom other GSM cells situated outside the cell cluster of the servingcell.

An important task for a GSM radio network operator is to reduce theamount of interference in the network. Clever frequency planning wherefrequencies are reused as sparsely as possible does this. However, sincethe traffic in GSM network increases, the frequencies must be reusedtighter and tighter and consequently with less distance (the reusedistance) between reuse of a frequency. This cause interference despiteclever frequency planning.

When the interference gets too high, there will be problems like droppedcalls, blocking and bad speech quality. In such areas a radio networkoperator wants to find the source of interference and rectify theproblem to improve speech quality and reduce dropped calls. A commontype of interference problem is co-channel interference. The interferingsignal originates from another base station, e.g. base station BS1 whichbelongs to the same operator. The interfering base station (BS1) isusing the same frequency as used in the serving cell and causesinterference.

In FIG. 2, GSM cells are represented with hexagons. The light grey cellis the serving cell (by the base station BS0 according to FIG. 1) andthe cross next to the light grey cell is the position where a mobilestation MS, served by the light grey cell, is experiencing aninterference problem. All dark grey cells, served by other base stationsBS1, BS2, . . . in FIG. 1 are using the frequency having interferenceproblems in the light grey cell. All of the dark grey cells are possiblesources of interference. The task is to identify the sources, or atleast reduce the number of candidates as much as possible.

Generally, a base station has a Base station Colour Code (BCC) and issending a training sequence, i.e. a signal pattern before and during acall in every burst which sequence is characteristic of that basestation. This sequence is the so called Training Sequence Code (TSC)used by a GSM-cell and which is known to the system serving the areashown in FIG. 2. Normally the TSC number and BCC are set to the samenumber so if the TSC of an interfering base station is known, also theBCC of that base station is known.

In a GSM-system, there are 26 symbols in the middle of the burst, theTSC, that are ordered in a predefined pattern. This sequence is normallyused by the equaliser in the mobile to estimate the channel throughwhich the signal has passed. There are eight different TSCs numbered 0to 7 and one C0 dummy TSC that is used on a C0 carrier with no traffic.By detecting which TSC the interferer uses together with the disturbedfrequency the cell configuration list can be searched for possiblecandidates. The knowledge about where the different candidates arelocated makes it possible to further eliminate some candidates.

The reason why it is so difficult to identify which TSC is used by theinterferer is that there is almost always a stronger signal present, thecarrier. The carrier dominates the received signal and makes itextremely hard to detect a pattern besides the carrier pattern itself.Therefore the first thing to do is to remove the carrier. The carrier ofthe received signal is not known but it can be estimated by taking thedetected bits and run them through a filter that models the physicalchannel.

An equaliser, a standard component in mobiles, performs the detection ofcarrier data. The whole carrier burst, data bits plus TSC, is then usedto produce a channel model. The channel model is for example a leastsquare (LS) estimate of an X-tap channel where X can be, for example,nine.

As mentioned earlier, the final estimated carrier is obtained byfiltering the carrier bits through the channel model. The estimatedcarrier is then removed from the received signal. Left in the remainingsignal should now be the interference signal and noise.

At this stage the focus can be set on finding which TSC that is used bythe interference source and how it is synchronised in time. This is doneby correlating the remaining signal against all TSCs and for all timeoffset. The TSC and offset that gives the highest correlation value isidentified and does most likely belong to the interferer. To achieve anystatistic stability the result from many correlations must beinterpreted together and presented in an easily understandable manner.

The method according to the invention can be divided in three mainsteps.

-   -   1. Carrier estimation and removal    -   2. Correlation of signal against all training sequences and        identification of interferer's BCC    -   3. Interferer candidate elimination

The interferer is identified through its training sequence and todetermine which training sequence an interferer uses the received signalis correlated against all known training sequences TKj (j=0,1,2,3, . . .7). To improve the result from the correlation and to reduce the numberof false peaks, the carrier is estimated and removed from the receivedsignal, see FIG. 3 which shows a block diagram illustrating theinventive method.

First of all it is determined if there is any carrier present to removeor not, block 1 in FIG. 3, and if it is, the sent data sequence isdetermined for example with a standard mobile equaliser, block 2. Achannel model, h, is produced by estimating the transfer function, forexample an LS-estimate, from sent data to received signal, block 3. Allsent symbols, not only the training sequence, are used to generate thechannel model. This to achieve a better channel estimate than theequaliser does. The carrier part in the received signal is obtained whenthe sent symbols are filtered through the channel model, block 4. Block5 is an ordinary AND-circuit.

Finally the estimated carrier is subtracted in a subtractor 6 from thereceived signal r leaving only the interferer and some noise, signal s.The remaining signal s after the carrier has been removed is used todetect the interferer's training sequence. The training sequence codenumber (0 . . . 7) is the same as the BCC number mentioned above. Thesearch for the training sequence code number is, as mentioned, done bycorrelation against the preknown training sequence patterns or byapplying some other equivalent operation on the remaining signal. Anidentification of the BCC is achieved by detecting the strongestcorrelation value of the different correlations, as will be described inconnection with FIG. 4.

The algorithm can be supplied with measurement data from a standardmobile. Measurement data is collected during drive tests in the areawhere interference problems have been registered. Since interferencephenomena are rather local in space, measurements should be performedwhen not moving or moving at low speed.

Data are collected in such a way that an interferer should be possibleto detect in an unsynchronised network. To assure that a whole TSC of aninterferer is received, at least 1½ carrier burst is sampled each timeand this is done a number of times per second.

At first, when the MS receives an interfered signal r, the carrier iseliminated giving a remaining signal s without any carrier as describedabove. The signal s is thereafter correlated with known trainingsequences for a number of offsets n=b 1,2,3, . . . , N i.e. s iscorrelated against TKj, where TKj are the j^(th) known trainingsequence.

This gives the following exemplary table: (I indicates strongcorrelation and X indicates very strong correlation). Signal s is thesignal which the training sequences are correlated against, where nindicates time offset relative to serving cell.) TABLE s(0) s(1) s(2)s(3) s(4) s(5) s(6) s(7) s(8) . . . s(N) TK0 0 0 0 I 0 0 0 0 0 0 TK1 0 00 0 0 0 I 0 0 0 TK2 0 0 0 I 0 0 0 0 0 0 TK3 0 I 0 0 0 X X 0 0 0 TK4 0 00 0 0 0 0 0 I I TK5 0 0 0 0 I 0 0 0 0 0 TK6 0 I I 0 0 0 0 0 0 0 TK7 0 00 0 0 0 0 0 I 0

In this case the strongest correlation was achieved for trainingsequence 3 at offset around 5 or 6.

Every position (marked with I, 0 or X) in the figure above is an averagemade over several bursts. This eliminates, or at least reduces, thefalse correlation peaks.

FIG. 4 shows in a diagram an example of correlation against differenttraining sequences. The signal s in which the carrier signal has beenremoved and which is disturbed by BS1 is correlated against TKa and TKb.This results in the curves A and B where a peak can be seen (indicatedby the arrow) in curve B. This indicates that the interference source isusing training sequence, curve B.

FIG. 5 shows a diagram of the training sequence with the highestcorrelation value plotted over time. To make a valid identification theresults from many samples must be interpreted together. The trainingsequence with the strongest correlation to the remaining signal isidentified for every sample and indicated with a short line. In thisexample it can be seen that most of the time the same training sequence(#1) is indicated.

FIG. 6 shows the percentage for a specified time window that a certaintraining sequence has had the strongest correlation. In this exampletraining sequence 1 has been identified in approximately 80% of thesamples.

From FIGS. 5 and 6 which are available to the operator (i.e. the personin vehicle MS), the BCC of the disturbing base station is determined.From a cell data base, also available to the operator, possiblecandidates are identified which are in accordance with the BCC and thedisturbed frequency.

The identified BCC will most of the time leave more than one possiblecandidate as source to the interference. According to a further featureof the present invention, the time offset and the fact that most of thecandidates transmit on more than one frequency is used to eliminate someof the candidates. First of all, the offset of the interferer relativeto the synchronisation channel is determined. Then, for all thefrequencies used by each and every of the candidates, measurements aremade to determine the offsets, relative to the synchronisation channel.If the offset for a signal on a certain frequency corresponds to theoffset of the identified interferer it is assumed to have the sameorigin and all cells not using this frequency can then be removed fromthe candidate list. This results in that the number of candidates can bereduced as long as the candidate cells contain different sets offrequencies.

FIG. 7 illustrates the timing offset of the training sequence forsignals on different frequencies. The frequencies on which offset ismeasured are the frequencies that are used by the different candidates.The offset is estimated through correlation against the known trainingsequence used by the interference source. As can be seen in the figurethe signals on frequencies fx, fy and fz have approximately the sameoffset as the identified interference source (f0). The offset of thesignals on frequencies fa, fb, fc, fp and fq deviate clearly from theoffset of the interference source. Since fx, fy and fz all belong tocandidate #3 it is the most probable interference source.

Merits of Invention

The basic problem, to identify the source of interference signals in aGSM radio network is solved by our solution. Carrier elimination is usedin our invention, which makes it possible to find interference signalswith low signal strength.

Channel estimation in our invention, based on all bits, makes theestimation accurate. The better channel estimation the better carrierelimination.

No need to measure timing data and store in database.

Timing data is measured when needed. This makes the invention robust—thecurrent network configuration and timing is used. Our invention isdifferent from solutions where a database with timing data is used. Thedatabase must be kept up to date, which is not an issue in ourinvention.

No need for continuous measurement (simple hardware is sufficient).

1-8. (Cancelled).
 9. A method to identify an interference source in amobile radio network, wherein a received signal consists of a wantedsignal and a number of interference signals of which one is a dominatinginterference signal and where all signals include a known trainingsequence, said method comprising the steps of: estimating the carrierand subtracting this carrier from the received signal; forming aremaining interference signal and correlating said interference signalagainst known training sequences, resulting in a determined trainingsequence associated with the interfering signal; finding anidentification code of a possible interference source from saiddetermined training sequence; determining a number of candidates fromsaid identification code, each of said candidates corresponding with acertain cell and the frequencies which are disturbed; determining thetiming offset for the frequencies used by said candidates; andinvestigating if one or more of these frequencies have the same timeoffset as the interference signal, whereby the at least one candidatewith the best offset matching of its frequencies in relation to othercandidates is identified as the interference source.
 10. The methodaccording to claim 9, wherein said step of forming a remaininginterference signal comprises the steps of: estimating both the trainingsequence and the data of the received signal; generating a channel modelby using said estimation of the training sequence and the data, saidchannel model being used to estimate the carrier; and subtracting theestimated carrier from the received signal, leaving the remaininginterference signal.
 11. The method as recited in claim 10, wherein saidestimated carrier is produced by filtering the estimated bits throughthe channel model obtained by said channel estimation.
 12. The method asrecited in claim 9, further comprising the steps of: determining thetime offset of the interfering signal; determining the time offset of aset of frequencies from each of said candidates; and comparing the timeoffset of said frequency set with the time offset of the identifiedinterferer, the candidate having the frequencies which best match saidfrequency set being identified as the interference source.
 13. Themethod as recited in claim 9, wherein the serving cell uses asynchronization channel, and wherein the step of investigating if one ormore of these signals have the same time offset as the interferencesignal further comprises the steps of: determining the time offset ofthe interfered signal relative to the synchronisation channel; andmeasuring the offset for all signals on said candidate's frequencies inrelation to said synchronization channel and, if the offset so measuredare the same for a number of said signals on certain frequencies, thesesignals are assumed to have the same origin and the frequencies can beassigned to what is considered to be the interfering source.
 14. Themethod as recited in claim 9, further comprising the steps of:calculating, for a defined time and for every training sequence, thepercent of interference of all samples for which the training sequencehad the strongest correlation; and, graphing the percent of interferencefor all training sequences.
 15. The method as claimed in claim 14,wherein, for every sample, said step of graphing identifies whichtraining sequence had the strongest correlation.
 16. The methodaccording to claim 12, wherein, to eliminate false interference sourcecandidates, said candidate cells contain different sets of frequencies,and wherein said method further comprises the step of removing all cellsnot using the frequency set whose offset corresponds to the offset ofthe identified interferer.